A dynamic logic for learning theory

Building on previous work [4,5] that bridged Formal Learning Theory and Dynamic Epistemic Logic in a topological setting, we introduce a Dynamic Logic for Learning Theory (DLLT), extending Subset Space Logics [18,10] with dynamic observation modalities [o]phi, as well as with a learning operator L((o) over right arrow), which encodes the learner's conjecture after observing a finite sequence of data (o) over right arrow. We completely axiomatise DLLT, study its expressivity and use it to characterise various notions of knowledge, belief, and learning. (C) 2019 Elsevier Inc. All rights reserved.